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Introduction: is data mining a methodological problem?

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  • Roger Backhouse
  • Mary Morgan

Abstract

This survey of the symposium papers argues that the problem of data mining should be of interest to both practicing econometricians and specialists in economic methodology. After summarizing some of the main points to arise in the symposium, it draws on recent work in the philosophy of science to point to parallels between data mining and practices engaged in routinely by experimental scientists. These suggest that data mining might be seen in a more positive light than conventional doubts about it imply.

Suggested Citation

  • Roger Backhouse & Mary Morgan, 2001. "Introduction: is data mining a methodological problem?," Journal of Economic Methodology, Taylor & Francis Journals, vol. 7(2), pages 171-181.
    • Handle: RePEc:taf:jecmet:v:7:y:2001:i:2:p:171-181
    DOI: 10.1080/13501780050045065
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    References listed on IDEAS

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    1. Hausman,Daniel M., 1992. "The Inexact and Separate Science of Economics," Cambridge Books, Cambridge University Press, number 9780521415019, December.
    2. Hausman,Daniel M., 1992. "The Inexact and Separate Science of Economics," Cambridge Books, Cambridge University Press, number 9780521425230, December.
    3. Roger E. Backhouse, 1997. "Truth and Progress in Economic Knowledge," Books, Edward Elgar Publishing, number 766.
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    Cited by:

    1. Thomas Mayer, 2006. "The Empirical Significance of Econometric Models," Working Papers 620, University of California, Davis, Department of Economics.
    2. Timothy Roth, 2001. "How science proceeds: the role of assumptions in the explanation of phenomena," Journal of Economic Methodology, Taylor & Francis Journals, vol. 8(3), pages 420-422.

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